Inflation, Forecast Intervals and Long Memory Regression Models
AbstractWe examine recursive out-of-sample forecasting of monthly postwarU.S. core inflation and log price levels. We use theautoregressive fractionally integrated moving average model withexplanatory variables (ARFIMAX). Our analysis suggests asignificant explanatory power of leading indicators associatedwith macroeconomic activity and monetary conditions forforecasting horizons up to two years. Even after correcting forthe effect of explanatory variables, there is conclusive evidenceof both fractional integration and structural breaks in the meanand variance of inflation in the 1970s and 1980s and weincorporate these breaks in the forecasting model for the 1980sand 1990s. We compare the results of the fractionally integratedARFIMA(0,d,0) model with those for ARIMA(1,d,1) models withfixed order of d=0 and d=1 for inflation. Comparing meansquared forecast errors, we find that the ARMA(1,1) model performsworse than the other models over our evaluation period 1984-1999.The ARIMA(1,1,1) model provides the best forecasts, but itsmulti-step forecast intervals are too large.
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Bibliographic InfoPaper provided by Tinbergen Institute in its series Tinbergen Institute Discussion Papers with number 01-029/4.
Date of creation: 14 Mar 2001
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- Bos, Charles S. & Franses, Philip Hans & Ooms, Marius, 2002. "Inflation, forecast intervals and long memory regression models," International Journal of Forecasting, Elsevier, vol. 18(2), pages 243-264.
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- Ball, Laurence & Mankiw, N Gregory, 1995.
"Relative-Price Changes as Aggregate Supply Shocks,"
The Quarterly Journal of Economics,
MIT Press, vol. 110(1), pages 161-93, February.
- Ball, L. & Mankiw, G.H., 1992. "Relative-Price Change as Aggregate Supply Shocks," Harvard Institute of Economic Research Working Papers 1609, Harvard - Institute of Economic Research.
- Laurence Ball & N. Gregory Mankiw, 1992. "Relative-Price Changes as Aggregate Supply Shocks," NBER Working Papers 4168, National Bureau of Economic Research, Inc.
- Laurence Ball & N. Gregory Mankiw, 1993. "Relative-price changes as aggregate supply shocks," Working Papers 93-13, Federal Reserve Bank of Philadelphia.
- Stock, James H. & Watson, Mark W., 1999.
Journal of Monetary Economics,
Elsevier, vol. 44(2), pages 293-335, October.
- Christoffersen, Peter F, 1998. "Evaluating Interval Forecasts," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 841-62, November.
- Ooms, Marius & Hassler, Uwe, 1997. "On the effect of seasonal adjustment on the log-periodogram regression," Economics Letters, Elsevier, vol. 56(2), pages 135-141, October.
- West, Kenneth D, 2001. "Tests for Forecast Encompassing When Forecasts Depend on Estimated Regression Parameters," Journal of Business & Economic Statistics, American Statistical Association, vol. 19(1), pages 29-33, January.
- Charles S. Bos & Philip Hans Franses & Marius Ooms, 1998.
"Long Memory and Level Shifts: Re-Analyzing Inflation Rates,"
Tinbergen Institute Discussion Papers
98-039/4, Tinbergen Institute.
- Philip Hans Franses & Marius Ooms & Charles S. Bos, 1999. "Long memory and level shifts: Re-analyzing inflation rates," Empirical Economics, Springer, vol. 24(3), pages 427-449.
- Franses, Ph.H.B.F. & Ooms, M. & Bos, C.S., 1998. "Long memory and level shifts: re-analysing inflation rates," Econometric Institute Research Papers EI 9811, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
- Harvey, David I & Leybourne, Stephen J & Newbold, Paul, 1998. "Tests for Forecast Encompassing," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(2), pages 254-59, April.
- David Harvey & Paul Newbold, 2000. "Tests for multiple forecast encompassing," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(5), pages 471-482.
- Lamoureux, Christopher G & Lastrapes, William D, 1990. "Persistence in Variance, Structural Change, and the GARCH Model," Journal of Business & Economic Statistics, American Statistical Association, vol. 8(2), pages 225-34, April.
- Sowell, Fallaw, 1992. "Maximum likelihood estimation of stationary univariate fractionally integrated time series models," Journal of Econometrics, Elsevier, vol. 53(1-3), pages 165-188.
- Jordi Galí & Mark Gertler, 1998.
"Inflation dynamics: A structural econometric analysis,"
Economics Working Papers
341, Department of Economics and Business, Universitat Pompeu Fabra.
- Gali, Jordi & Gertler, Mark, 1999. "Inflation dynamics: A structural econometric analysis," Journal of Monetary Economics, Elsevier, vol. 44(2), pages 195-222, October.
- Jordi Gali & Mark Gertler, 2000. "Inflation Dynamics: A Structural Econometric Analysis," NBER Working Papers 7551, National Bureau of Economic Research, Inc.
- Hassler, Uwe & Wolters, Jurgen, 1995. "Long Memory in Inflation Rates: International Evidence," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(1), pages 37-45, January.
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